Ontology is Overrated: Categories, Links, and Tags - Clay Shirky

Based on two talks I gave in the spring of 2005—one entitled "Ontology Is Overrated", and one entitled "Folksonomies & Tags: The rise of user-developed classification."

Under Maintenance

Traité de documentation : le livre sur le livre, théorie et pratique

Traité de documentation : le livre sur le livre, théorie et pratique Les livres et les documents; La lecture, le consultation et la documentation; Rédaction, multiplication, description, classement, conservation, utilisation des documents; Edition et librairie, bibliographie, bibliothèque, encyclopédie, archives, muséographie documentaire, documentation administrative; Organismes, organisation, coopération, Office et Institut international de bibliographie et de documentation; Réseau universel d'information et de documentation

Locking the Web Open, a Call for a Decentralized Web - Internet Archive Blogs

Presentation by Brewster Kahle, Internet Archive Digital Librarian at Ford Foundation NetGain gathering, — a call from 5 top foundations to think big about prospects for our digital future. (More detailed version) Hi, I’m Brewster Kahle, Founder of the Internet Archive. For 25 years we’ve been building this fabulous thing—the Web. I want to talk

Introducing the Knowledge Graph: things, not strings

We hope this will give you a more complete picture of your interest, provide smarter search results, and pique your curiosity.

Understanding Knowledge as a Commons: From Theory to Practice

Looking at knowledge as a shared resource: experts discuss how to define, protect, and build the knowledge commons in the digital age.Knowledge in digital

Named graphs, provenance and trust

Information accountability

With access control and encryption no longer capable of protecting privacy, laws and systems are needed that hold people accountable for the misuse of personal information, whether public or secret.

Semantics and complexity of SPARQL

SPARQL is the standard language for querying RDF data. In this article, we address systematically the formal study of the database aspects of SPARQL, concentrating in its graph pattern matching facility. We provide a compositional semantics for the core part of SPARQL, and study the complexity of the evaluation of several fragments of the language. Among other complexity results, we show that the evaluation of general SPARQL patterns is PSPACE-complete. We identify a large class of SPARQL patterns, defined by imposing a simple and natural syntactic restriction, where the query evaluation problem can be solved more efficiently. This restriction gives rise to the class of well-designed patterns. We show that the evaluation problem is coNP-complete for well-designed patterns. Moreover, we provide several rewriting rules for well-designed patterns whose application may have a considerable impact in the cost of evaluating SPARQL queries.

From Freebase to Wikidata: The Great Migration

The entity-relationship model—toward a unified view of data

A data model, called the entity-relationship model, is proposed. This model incorporates some of the important semantic information about the real world. A special diagrammatic technique is introduced as a tool for database design. An example of database design and description using the model and the diagrammatic technique is given. Some implications for data integrity, information retrieval, and data manipulation are discussed. The entity-relationship model can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model. Semantic ambiguities in these models are analyzed. Possible ways to derive their views of data from the entity-relationship model are presented.

Industry-scale knowledge graphs: lessons and challenges

Five diverse technology companies show how it's done.

Local-first software: you own your data, in spite of the cloud

Knowledge Graphs

In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.

A relational model of data for large shared data banks

Future users of large data banks must be protected from having to know how the data is organized in the machine (the internal representation). A prompting service which supplies such information is not a satisfactory solution. Activities of users at terminals and most application programs should remain unaffected when the internal representation of data is changed and even when some aspects of the external representation are changed. Changes in data representation will often be needed as a result of changes in query, update, and report traffic and natural growth in the types of stored information. Existing noninferential, formatted data systems provide users with tree-structured files or slightly more general network models of the data. In Section 1, inadequacies of these models are discussed. A model based on n -ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced. In Section 2, certain operations on relations (other than logical inference) are discussed and applied to the problems of redundancy and consistency in the user's model.